In android app i have this case:
Listen to my editText with observable:
WidgetObservable.text(myEditText, false)
.map { it.text().toString() }
.debounce(800, TimeUnit.MILLISECONDS, Schedulers.io())
Then i need to send network request with string emitted by observable:
.flatMap { networkObservable.subscribeOn(Schedulers.io()) }
My question is: what is the best possible way to write infinite stream of these network results.
Errors handled by UI.
Unsubscription done with AppObservable.bindActivity() wrapper
I ended up attaching materialize() operator to network observable, and then handling it like:
.subscribe{
when (it.getKind()) {
Kind.OnNext -> text.setText(it.getValue())
Kind.OnError -> text.setText(it.getThrowable().getMessage())
}
}
Do you know better way, or its just fine?
At least it works.
P.S. another useful case will be Refresh button clicks flatMap'ed to network calls
You can use onErrorResumeNext to recovery your Observable from a failure. E.g.,
WidgetObservable.text(myEditText, false)
.map { it.text().toString() }
.debounce(800, TimeUnit.MILLISECONDS, Schedulers.io())
.flatMap {
networkObservable.subscribeOn(Schedulers.io())
.onErrorResumeNext(t -> t.getMessage())
}
Related
I need make two parallel requests with RxJava. For this I use zip operator. Here is my code:
public Disposable getBooksAndAuthors(String id, ReuqestCallback requestCallback) {
return singleRequest(Single.zip(
getBooks(id).subscribeOn(Schedulers.newThread()).observeOn(AndroidSchedulers.mainThread()),
getAuthors(id).subscribeOn(Schedulers.newThread()).observeOn(AndroidSchedulers.mainThread()),
(book, author) -> new ZipResponseWrapper(book, author).getResponse()), requestCallback);
}
private <T extends NetworkResponse> Disposable singleRequest(Single<T> single, RequestCallback requestCallback) {
return single.doOnSubscribe(d -> requestCallback.onStartRequest())
.doOnSuccess(s -> requestCallback.onSuccess(s))
.doOnError(ErrorConsumer.consume((t) -> requestCallback.onError(t)))
.doFinally(() -> requestCallback.onFinish())
.subscribe();
}
But I don’t understand how to receive response separately for each request. That is, I need to, if the answer came to the first request, immediately display the data received from this request and not wait for a response to the second request. And after the answer to the second request arrives, display the data received on the second request.This is necessary due to the fact that the second request fulfills a long time. Please help me.
Here is an example of how you can handle it with the responses for each function:
val disposable = Observable.zip(
firstNetworkCall().subscribeOn(Schedulers.io()),
secondNetworkCall().subscribeOn(Schedulers.io()),
BiFunction{
firstResonse: ResponseOneType,
secondResponse: ResponseTwoType ->
combineResult(firstResponse, secondResponse) }))
.observeOn(AndroidSchedulers.mainThread())
.subscribe { it -> doSomethingWithIndividualResponse(it) }
My suggestion (in Kotlin though):
val id = 0L
Observables.combineLatest(
getBooks(id).startWith(emptyList<Book>()).subscribeOn(Schedulers.io()).observeOn(Schedulers.computation()),
getAuthor(id).startWith(emptyList<Author>()).subscribeOn(Schedulers.io()).observeOn(Schedulers.computation())
) { book: List<Book>, author: List<Author> ->
Pair(book, author)
}.skip(1)
.observeOn(AndroidSchedulers.mainThread())
.subscribe { (books: List<Book>, authors: List<Author>) ->
view.show(books)
view.show(authors)
}
I have This method that calls a Rest API and returns the result as an Observable (Single):
fun resetPassword(email: String): Single<ResetPassword> {
return Single.create { emitter ->
val subscription = mApiInterfacePanda.resetPassword(email)
.observeOn(AndroidSchedulers.mainThread())
.subscribeOn(Schedulers.io())
.subscribe({ resetPasswordResponse ->
when(resetPasswordResponse.code()) {
200 -> {
resetPasswordResponse?.body()?.let { resetPassword ->
emitter.onSuccess(resetPassword)
}
}
else -> emitter.onError(Exception("Server Error"))
}
}, { throwable ->
emitter.onError(throwable)
})
mCompositeDisposable.add(subscription)
}
}
Unit Test:
#Test
fun resetPassword_200() {
val response = Response.success(200, sMockResetPasswordResponse)
Mockito.`when`(mApiInterfacePanda.resetPassword(Mockito.anyString()))
.thenReturn(Single.just(response))
mTokenRepository.resetPassword(MOCK_EMAIL)
val observer = mApiInterfacePanda.resetPassword(MOCK_EMAIL)
val testObserver = TestObserver.create<Response<ResetPassword>>()
observer.subscribe(testObserver)
testObserver.assertSubscribed()
testObserver.awaitCount(1)
testObserver.assertComplete()
testObserver.assertResult(response)
}
My Problem is only this line gets covered and the other lines won't run and that has a lot of impact on my total test coverage:
return Single.create { emitter ->
There's more than one thing going on here if I'm not mistaken. Let's take it in parts.
First, your "internal" observer:
mApiInterfacePanda.resetPassword(email)
.observeOn(AndroidSchedulers.mainThread())
.subscribeOn(Schedulers.io())
.subscribe({ resetPasswordResponse -> ... })
Is observing on the android main thread and executing on a background thread. To the best of my knowledge, in most cases, the test thread will end before your mApiInterfacePanda .resetPassword has a chance to finish and run. You didn't really post the test setup, so I'm not sure if this is an actual issue, but in any case it's worth mentioning. Here's 2 ways to fix this:
RxJavaPlugins and RxAndroidPlugins
RxJava already provides a way to change the schedulers that are provided. An example is RxAndroidPlugins.setMainThreadSchedulerHandler. Here's how it could help:
#Before
fun setUp() {
RxAndroidPlugins.setInitMainThreadSchedulerHandler { Schedulers.trampoline() }
RxJavaPlugins.setInitIoSchedulerHandler { Schedulers.trampoline() }
}
The above methods make sure that everywhere you use the main thread scheduler and the io scheduler, it'll instead return the trampoline scheduler. This is a scheduler that guarantees that the code is executed in the same thread that was executing previously. In other words, it'll make sure you run it on the unit test main thread.
You will have to undo these:
#After
fun tearDown() {
RxAndroidPlugins.reset()
RxJavaPlugins.reset()
}
You can also change other schedulers.
Inject the schedulers
You can use kotlin's default arguments to help out with injecting schedulers:
fun resetPassword(
email: String,
obsScheduler: Scheduler = AndroidSchedulers.mainThread(),
subScheduler: Scheduler = Schedulers.io()
): Single<ResetPassword> {
return Single.create { emitter ->
val subscription = mApiInterfacePanda.resetPassword(email)
.observeOn(obsScheduler)
.subscribeOn(subScheduler)
.subscribe({ resetPasswordResponse ->
when(resetPasswordResponse.code()) {
200 -> {
resetPasswordResponse?.body()?.let { resetPassword ->
emitter.onSuccess(resetPassword)
}
}
else -> emitter.onError(Exception("Server Error"))
}
}, { throwable ->
emitter.onError(throwable)
})
mCompositeDisposable.add(subscription)
}
}
At test time you can just call it like resetPassword("foo#bar.com", Schedulers.trampoline(), Schedulers.trampoline() and for the application just pass in the email.
The other thing I see here is maybe not related to the problem, but I think it's still good to know. First, you're creating a single, but you don't need to do this.
Single.create is usually used when you don't have reactive code. However, mApiInterfacePanda.resetPassword(email) already returns a reactive component and although I'm not sure, let's just assume it's a single. If not, it should be fairly simple to convert it to something else.
You're also holding on to a disposable, which from what I can tell shouldn't be necessary.
Lastly, you're using retrofit according to your tags so you don't need to make the call return a raw response unless extremely necessary. This is true because retrofit checks the status code for you and will deliver the errors inside onError with an http exception. This is the Rx way of handling the errors.
With all this in mind, I'd rewrite the entire method like this:
fun resetPassword(email: String) = mApiInterfacePanda.resetPassword(email)
(note that resetPassword must not return a raw response, but Single<ResetPassword>
It actually shouldn't need anything else. Retrofit will make sure things end up in either onSuccess or onError. You don't need to subscribe to the result of the api here and handle disposables - let whoever is calling this code handle it.
You may also notice that if this is the case, then the solution for the schedulers is not needed. I guess this is true in this case, just remember some operators operate in some default schedulers and you may need to override them in some cases.
So how would I test the above method?
Personally I'd just check if the method calls the api with the right parameters:
#Test
fun resetPassword() {
mTokenRepository.resetPassword(MOCK_EMAIL)
verify(mApiInterfacePanda).resetPassword(MOCK_EMAIL)
}
I don't think there's much more needed here. There's no more logic I can see in the rewritten method.
I'm using RxKotlin to build out my latest Android app, and I've come up against a familiar issue: how to handle network errors in an Rx-like way.
I have a stream set up for search terms against a TextView like this:
searchBar
.queryTextObservable()
.debounce(500, TimeUnit.MILLISECONDS)
.map { it.trim() }
.filter { it.isNotBlank() }
.observeOn(Schedulers.io())
This is a useful way to listen against changes to text input, so I then extend the code to feed the prepared text into a network request (using the Retrofit library with the RxJava extension) to search against:
searchBar
.queryTextObservable()
.debounce(500, TimeUnit.MILLISECONDS)
.map { it.trim() }
.filter { it.isNotBlank() }
.observeOn(Schedulers.io())
.switchMap { search(it) }
.observeOn(AndroidSchedulers.mainThread())
.subscribeOn(AndroidSchedulers.mainThread())
.subscribe(...)
The problem happens when there's a network error - my entire subscription is cancelled. It seems like I have some options to manage the failure, but none of them seem very clean:
Have an inner observable after text input is complete that makes the network request
Use onErrorResumeNext and pass a sentinel value
This is obviously not exhaustive, but what is the appropriate pattern(s) to gracefully handle network errors while preserving the stream (and hence the usefulness) of user input from the search bar?
Using operators such as onErrorReturn is a pretty standard approach if you look at reactive patterns which provide a unidirectional data flow such as MVI.
Following such patterns you typically map the state of your network call into an object which represents the state of the call.
A simple example without any MVx patterns would look something like below, where the observable from your RXBinding invokes a call to the API, but instead of just returning the data from the API it returns a state object which can then be rendered on screen.
private val disposables = CompositeDisposable()
override fun onStart() {
super.onStart()
disposables.add(
RxView.clicks(load_data_button)
.flatMap { requestData() }
.observeOn(AndroidSchedulers.mainThread())
.subscribe(this::renderRequestState)
)
}
override fun onStop() {
disposables.clear()
super.onStop()
}
private fun requestData(): Observable<RequestState> {
return myApi.requestData()
.toObservable()
.subscribeOn(Schedulers.io())
.map<RequestState>(RequestState::Success)
.onErrorReturn(RequestState::Error)
.startWith(RequestState.InFlight)
}
private fun renderRequestState(requestState: RequestState) {
when (requestState) {
RequestState.InFlight -> showProgress()
is RequestState.Success -> showResult(requestState.result)
is RequestState.Error -> showError(requestState.error)
}
}
sealed class RequestState {
object InFlight : RequestState()
data class Success(val result: MyData) : RequestState()
data class Error(val error: Throwable) : RequestState()
}
Hannes Dorfmann wrote a great set of articles on the MVI pattern which utilises this approach.
http://hannesdorfmann.com/android/model-view-intent
http://hannesdorfmann.com/android/mosby3-mvi-1
Hi i am trying to implement a Single observable that chains two requests together.
In between the two requests i make, i notify a callback to update the UI with the response from request one and then launch the next request in the Schedulaers.io thread.
The issue i am having is that it tries to update the UI from the schedulars.io thread too and results to nothing being updated in the ui thread.
i cold wrap the calback on RunOnUiThread code block in android but wondering if there is a more elegant way of doing it?
i checked couroutines and it seems to just deal with putting a block of code in a seperate thread.
Here is my current code
override fun getHomeScreenInformation() {
delegator.requestOne()
.flatMap { responseOne->
homeScreenCallBack.onResponseOneRecieved(responseOne)
delegator.requestTwo()
}
.observeOn(AndroidSchedulers.mainThread())
.subscribeOn(Schedulers.io())
.subscribe(
{responseTwo-> homeScreenCallBack.onResponseTwoRecieved(responseTwo)},
{error -> homeScreenCallBack.onError()}
)
}
Apply observeOn(AndroidSchedulers.mainThread()) as many times as necessary:
delegator.requestOne()
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread()) // <----------------------
.flatMap { responseOne ->
homeScreenCallBack.onResponseOneRecieved(responseOne)
delegator.requestTwo()
.subscribeOn(Schedulers.io()) // <----------------------
}
.observeOn(AndroidSchedulers.mainThread())
.subscribe(
{responseTwo-> homeScreenCallBack.onResponseTwoRecieved(responseTwo)},
{error -> homeScreenCallBack.onError()}
)
Here's a simplified version of what I'm trying to do (using Kotlin and RxJava)
makeServerCall()
.doOnNext {
doStuff(it)
}
//TODO: if it == 0, call asyncOperation() and wait for its callback to fire
//before running the rest of the stream. Otherwise immediately run the rest
//of the stream
.flatMap {
observable1(it)
observable2(it)
Observable.merge(
getSpotSearchObservable(observable1),
getSpotSearchObservable(observable2)
}
.subscribeBy(onNext = {
allDone()
view?
})
How do I squeeze in the call to asyncOperation() and make the rest of the stream wait for its callback to fire, but only when a certain condition is met? This seems like it's probably a trivial operation in Rx, but no obvious solution is coming to mind.
FlatMap it!
.flatMap {
if (it == 0) {
return#flatMap asyncOperation()
.ignoreElements()
.andThen(Observable.just(0))
}
return#flatMap Observable.just(it)
}
.flatMap {
observable1(it)
observable2(it)
Observable.merge(
getSpotSearchObservable(observable1),
getSpotSearchObservable(observable2)
)
}